IBM's Predictions: 6 Big Data Trends In 2014

A big data expert shares predictions based on feedback from IBM's enterprise clients. Is it time to update your strategy?

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Businesses next year will sharpen their focus on big data and place a greater emphasis on analytics projects, data-related security and privacy, and a new generation of cognitive-intelligence apps. They will even find a seat at the boardroom table for a new executive: the Chief Data Officer.

That's according to Inhi Suh, IBM vice president of big data, integration, and governance. Her 2014 predictions are based, in part, on feedback that IBM is getting from its enterprise clients. Here are six ways that organizations will react to the big data phenomenon next year, according to Suh.

2. Businesses get serious about big data privacy and security. Organizations in 2014 will make a greater effort to build security, privacy, and governance policies into their big data processes. This might involve a careful balancing act, as business devises innovative, data-driven projects that deliver usable insights while addressing security threats that might arise.

3. A bigger investment in big data. Big data insights aren't free, of course, particularly when they involve spending real money on a Hadoop platform. But that won't stop companies from investing in big data platforms. New applications in 2014 will enable a wider range of analytics, including "reporting, dashboards and planning, predictive analytics, recommendations, and new cognitive capabilities" for transactional, social, mobile, and other data types, says Suh.

4. Welcome, Chief Data Officer. It seems there's room for one more at the top. More organizations in 2014 will bring a chief data officer (CDO) on board. As the title implies, this new member of the C-suite will be the enterprise's "champion of data" and find ways to extract those all-important insights from new forms of digital information. IBM cites Gartner statistics that show some 100-plus CDOs serve in large enterprises today, more than twice the number in 2012.

5. Smarter big data apps. Plenty of software firms are working on big data apps designed to bring the power of analytics to the masses, ideally reducing an organization's reliance on highly trained, highly paid data scientists. Next year will bring a "new ecosystem" of developers, ISVs, and startups that create a new class of cognitive computing apps, says Suh. These programs will learn and improve with experience, thereby helping organizations solve complex questions.

6. Outside data is as important as inside data. As every big data watcher knows, the explosive growth of social media, mobile devices, and machine sensors is generating a wealth of bits that either didn't exist or weren't accessible a few years ago. Some of this data is generated within an organization, but a larger percentage comes from the outside -- Twitter streams, for instance.

In 2014, businesses will find more ways to harness this mix of structured and unstructured data, ideally helping them better address the needs of their employees and customers. Customer service pros, for instance, might increasingly analyze social media feeds to respond more quickly to consumer reactions (especially the bad ones). And human resource teams might mine data shared by employees to more effectively recruit, develop, and retain top talent, says Suh.

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The shift from gut based decision making to analytics based decisions is a major cultural shift for executives who do not have a full appreciation of how many of their business decisions are influenced by emotional factors or who don't regularly engaged in a disciplined rational analysis of their options. There also needs to be an openess to what analytics reveal since the opportunity to include unstructured data will provide new insights that may be counter to their intuition. As well, the frequency of business decision may increase as the impacts of decisions or trends in the market are revealed in real time versus monthly or quarterly reporting cycles. This may require exploring a new balance between sticking with the plan and being responsive

I share the idea of Susan, support a CDO can provide decision-making is also the complement of the current CIO IT, because this latter task should be focused on the research and implementation of new technologies to support the business, but the function is the CDO interpretración the fact that through technology can process better and faster. Definitely complement.

Why do you see the CDO as rival of the CIO? The IT departments are getting overloaded these days with all the different technologies the enterprises are deploying. Having a data scientist's voice in the boardroom aliviates all the responsibility many CIOs have today.

More than rivals I believe they should be seen as two captains sailing the same huge boat, where only one captain in not enough anymore.

Something had better change in security. The current models have been out striped, outpaced and out flanked by mobile and the Internet of Things is only going to make it worse. The is one of the pitfalls of consumer tech over enterprise tech. Enterprise usually has their ducks in a row before they deploy. Consumer tech/tech du jour, races ahead of any consideration of procedure, process, or impact. Improved security will help enhance privacy, but I fear that may be a lost cause.

This CDO vs. CIO rivalry does not look to go away anytime soon. Interesting that IBM sees it in the field as well. Readers, is your IT organization feeling power shift away from the CIO and to the CDO -- or is your company looking to add a CDO in 2014?

One of the trend, i see around me is Smarter big data apps, we have been discussing about such kind of applications, but there is still no clarity on what exactly we expect these applications to do for us.

Most IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.

Why should big data be more difficult to secure? In a word, variety. But the business won’t wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.